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Interactive Histology of Large-Scale Biomedical Image Stacks

Won-Ki Jeong, Jens Schneider, Stephen G. Turney, Beverly E. Faulkner-Jones, Dominik Meyer, Rudiger Westermann, R. Clay Reid, Jeff Lichtman, Hanspeter Pfister

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Tags: Image processing, Medicine, nVidia, nVidia GeForce GTX 285, OpenGL, Texture detection, Visualization

June 17, 2011 by hgpu

Multi-scale neural texture classification using the GPU as a stream processing engine

M. Martinez-Zarzuela, F. Diaz-Pernas, M. Anton-Rodriguez, J. Diez-Higuera, D. Gonzalez-Ortega, D. Boto-Giralda, F. Lopez-Gonzalez, I. De La Torre

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Tags: Cg, Computer science, nVidia, nVidia GeForce 8800 GTX, OpenGL, Texture detection

November 16, 2010 by hgpu

Tilus: A Tile-Level GPU Kernel Programming Language

Tilus: A Tile-Level GPGPU Programming Language for Low-Precision Computation

Memory-Efficient Acceleration of Block Low-Rank Foundation Models on Resource Constrained GPUs

BoltzGen:Toward Universal Binder Design

CUDA-L2: Surpassing cuBLAS Performance for Matrix Multiplication through Reinforcement Learning

cuPilot: A Strategy-Coordinated Multi-agent Framework for CUDA Kernel Evolution

MATLAB Tensor Core models

Accurate Models of NVIDIA Tensor Cores

TritonForge: Transform PyTorch Operations into Optimized GPU Kernels with LLMs

TritonForge: Profiling-Guided Framework for Automated Triton Kernel Optimization

RLTune: Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

tritonBLAS: A Lightweight Triton-based General Matrix Multiplication (GEMM) Library

tritonBLAS: Triton-based Analytical Approach for GEMM Kernel Parameter Selection

hls4ml: Machine learning on FPGAs using HLS

hls4ml: A Flexible, Open-Source Platform for Deep Learning Acceleration on Reconfigurable Hardware

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